




'''simple docstring'''


from random import randint, random


def     SCREAMING_SNAKE_CASE							(   a_						:				int					,       a_						:				int					,       a_						:				int					,       a_						:				bool = False					,       a_						:				bool = False					,       a_						:				int = 5					,       ):
  __a								=       [[-1] * number_of_cells]  # Create a highway without any car
  __a								=       0
  __a								=       max(a_					,       0      )
  while i < number_of_cells:
    __a								=       (
        randint(0					,       a_      ) if random_speed else initial_speed
    )  # Place the cars
    i += (
        randint(1					,       max_speed * 2      ) if random_frequency else frequency
    )  # Arbitrary number, may need tuning
  return highway


def     SCREAMING_SNAKE_CASE							(   a_						:				list					,       a_						:				int      ):
  __a								=       0
  __a								=       highway_now[car_index + 1 :]
  for cell in range(len(a_      )      ):  # May need a better name for this
    if cells[cell] != -1:  # If the cell is not empty then
      return distance  # we have the distance we wanted
    distance += 1
  # Here if the car is near the end of the highway
  return distance + get_distance(a_					,       -1      )


def     SCREAMING_SNAKE_CASE							(   a_						:				list					,       a_						:				float					,       a_						:				int      ):
  __a								=       len(a_      )
  # Beforce calculations, the highway is empty
  __a								=       [-1] * number_of_cells

  for car_index in range(a_      ):
    if highway_now[car_index] != -1:
      # Add 1 to the current speed of the car and cap the speed
      __a								=       min(highway_now[car_index] + 1					,       a_      )
      # Number of empty cell before the next car
      __a								=       get_distance(a_					,       a_      ) - 1
      # We can't have the car causing an accident
      __a								=       min(next_highway[car_index]					,       a_      )
      if random() < probability:
        # Randomly, a driver will slow down
        __a								=       max(next_highway[car_index] - 1					,       0      )
  return next_highway


def     SCREAMING_SNAKE_CASE							(   a_						:				list					,       a_						:				int					,       a_						:				float					,       a_						:				int      ):
  __a								=       len(highway[0]      )

  for i in range(a_      ):
    __a								=       update(highway[i]					,       a_					,       a_      )
    __a								=       [-1] * number_of_cells

    for car_index in range(a_      ):
      __a								=       next_speeds_calculated[car_index]
      if speed != -1:
        # Change the position based on the speed (with % to create the loop)
        __a								=       (car_index + speed) % number_of_cells
        # Commit the change of position
        __a								=       speed
    highway.append(a_      )

  return highway


if __name__ == "__main__":
  import doctest

  doctest.testmod()









'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_					=   {
    "configuration_clap": [
        "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ClapAudioConfig",
        "ClapConfig",
        "ClapTextConfig",
    ],
    "processing_clap": ["ClapProcessor"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_					=   [
      "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
      "ClapModel",
      "ClapPreTrainedModel",
      "ClapTextModel",
      "ClapTextModelWithProjection",
      "ClapAudioModel",
      "ClapAudioModelWithProjection",
  ]
  UpperCAmelCase_					=   ["ClapFeatureExtractor"]

if TYPE_CHECKING:
  from .configuration_clap import (
      CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
      ClapAudioConfig,
      ClapConfig,
      ClapTextConfig,
  )
  from .processing_clap import ClapProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_clap import ClapFeatureExtractor
    from .modeling_clap import (
        CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
        ClapAudioModel,
        ClapAudioModelWithProjection,
        ClapModel,
        ClapPreTrainedModel,
        ClapTextModel,
        ClapTextModelWithProjection,
    )


else:
  import sys

  UpperCAmelCase_					=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



